The motivation of the tracklet booster is simple yet effective. We take the tracklets from any tracklet generators [1]}, [2]}, [3]} or preliminary tracking results as the input. Due to matching errors, a tracklet may contain multiple object IDs. To clean the IDs within the tracklet, Splitter is proposed to split tracklets into small pieces on the potential ID-switch positions to ensure split tracklets have purer IDs as much as possible. Next, the split tracklets are sent into Connector to learn representative embeddings. Finally, the tracklets with the similar embeddings are grouped to form clusters, i.e., to generate the final entire track. The framework of the tracklet booster is shown in Figure REF . The details of Splitter and Connector are demonstrated in the following sub-sections.
